Posts in category English

Passenger Travel Time Reliability for Multi-Modal Public Transport Journeys

Urban transit networks typically consist of multiple modes and the journeys may involve a transfer within or across modes. Hence, the passenger experience of travel time reliability is based on the whole journey experience including the transfers. Although the impact of transfers on reliability has been highlighted in the literature, the existing indicators either focus on uni-modal transfers only or fail to include all components of travel time in reliability measurement. This study extends the existing ‘Reliability Buffer Time’ metric to journeys with multi-modal transfers and develops a methodology to calculate it using a combination of smartcard and automatic vehicle location data. The developed methodology is applied to a real-life case study for the Amsterdam transit network consisting of bus, metro and tram services. By using a consistent method for all journeys in the network, reliability can be compared between different modes or between multiple routes for the same origin-destination pair. The developed metric can be used to study the reliability impacts of policies affecting multiple modes. It can also be used as an input to behavioral models such as mode, route or departure time choice models.

Find the TRB paper and presentation of Malvika Dixit HERE and HERE

Understanding the difference in travel patterns between docked and dockless bike-sharing systems: a case study in Nanjing, china

The co-existence of dockless and traditional docked bike-sharing systems presents new opportunities for sustainable transportation in cities all over the world, both serving door to door trips and access and egress to and from transit. To compare travel patterns of these two systems, we explored the GPS data of a dockless bike-sharing scheme and the smart card data of a docked bike-sharing scheme in the city of Nanjing, China over the same time period. In order to obtain information from different perspectives, such as user perception and opinions, an intercept survey on bike-sharing mode choice was conducted. A mode choice model was estimated to reveal the effects of personal information, user perception and experience on bike-sharing usage. Results show that dockless bike-sharing systems have a shorter average travel distance and travel time but a higher use frequency and hourly usage volume compared to docked bike-sharing systems. Trips of docked and dockless bike-sharing on workdays are more frequent than those on weekends, especially during the morning and evening rush hours from 7:00-9:00 and 17:00-19:00, respectively. As to the factors influencing travelers’ mode choice, results show that retirees, enterprise staff and users with E-bikes are less likely to use docked sharing-bikes than dockless bikes. In contrast, high-income travelers and people who are highly sensitive to discounts, internet technology and online payment service are more likely to use the dockless bike-sharing. Finally, policy implications are discussed for cities to improve the performance of docked and dockless bike-sharing systems.

Find our poster HERE

Operations of zero-emission buses: impacts of charging methods and mechanisms on costs and the level of service

To limit global warming and strive for more liveable and sustainable cities, innovative zero-emission buses are on the rise all around the world. For now, only trolley, battery and fuel-cell electric vehicles can be classified as (on the pipe) zero-emission vehicles. Different charging methods, including different charging systems and power, are available to charge battery electric vehicles. However, scientific literature focused on the operation and charging scheduling of electric vehicles is scarce.
In this study, a comparison of different applied charging methods for electric buses is obtained. A new ZE-bus station simulation method is developed to assess charging methods and charging regulations with regard to their impacts on costs and level of service.
The shift to zero emission bus transport is meant for achieving more sustainable and liveable cities. However, this research concludes that this is involved with higher costs and passenger disturbances. The investment costs increase substantially. Benefits of electric operations, including vehicle propulsion cost savings up to 70 percent, are not able to compensate these high investments. (Slow) depot charging offers opportunities for operations on short distance lines. The depot location should be close to a bus station and additional fleet is required. In order to prevent fleet overcapacity, vehicles should be recharged with high charging power along the line, preferably at combined bus stations and terminals in order to prevent charging related delays. Dynamic/In-motion charging – still in its infancy stage yet – offers opportunities to prevent these delays due to combined charging and operation time.

Find the TRB paper and poster of Max Wiercx HERE and HERE

Robust Control for Regulating Frequent Bus Services: Supporting the Implementation of Headway-based Holding Strategies

Reliability is a key determinant of the quality of a transit service. Control is needed in order to deal with the stochastic nature of high-frequency bus services and to improve service reliability. In this study, we focus on holding control, both schedule- and headway-based strategies. An assessment framework is developed to systematically assess the effect of different strategies on passengers, the operator and transport authority. This framework can be applied by operators and authorities in order to determine what holding strategy is most beneficial to regulate headways, and thus solve related problems. In this research knowledge is gained about what service characteristics affect the performance of holding strategies and the robustness of these strategies in disrupted situations, by using scenarios. The framework is applied to a case study of a high-frequency regional bus line in the Netherlands. Based on the simulation results, we identified the line characteristics that are important for the performance of schedule- and headway-based strategies and determined how robust different strategies are in case of disruptions. Headway-based control strategies better mitigate irregularity along the line, especially when there are disruptions. However, schedule-based control strategies are currently easier to implement, because it does not require large changes in practice, and the performance of both strategies is generally equal in regular, undisrupted situations. In this paper, insights into what the concerns are for operators with respect to technical adaptations, logistical changes and behavioral aspects when using a headway-based strategy are given.

Find the TRB paper and presentation of Ellen van der Werff HERE and HERE

UITP INDIA SEMINAR ON URBAN RAIL NETWORK – BUILDING SUSTAINABLE CITIES

Transport infrastructure is one of the most important factors for a country’s progress. To keep this faster pace, for moving people, urban rail projects are playing a crucial role not only as a transportation solution but as a means to transform cities. 52.8% of India’s population would be living in cities and towns by mid-century compared to 32.8% in 2015, i.e. more than 750 million inhabitants.
Urban rail networks are expanding in Indian cities, as these are becoming key lifeline for the cities. Currently, 490 km of metro lines are operational in 10 different cities in the country. More than 600 km of metro rail projects are under construction in various cities. Further, It is expected that more than 350 km of new construction will be started in the next few years as more and more cities are planning for expansion or new constructions of metro rail. The average budget outlay of Govt. of India is likely to increase to about INR 250 billion annually, apart from the investments envisaged by the state governments, private partners and Urban Local Bodies (ULBs). Government of India has sanctioned at least INR 306.53 billion to Metro projects across the country between the periods of 2012-16.

Find my contributions here: Transit data and Transit system choice and lightrail

Improving railway passengers experience: two perspectives

This paper describes two perspectives to improve the passenger experience. The passenger satisfaction pyramid is introduced, consisting of the base of the pyramid (dissatisfiers) focusing on time well saved and the top of the pyramid (satisfiers) aiming at time well spent. The challenge in planning and design of public transport services is to find the most efficient (set of) design choices. Depending on the context this might either mean focusing on the top or on the bottom of the pyramid. We found that influencing and enhancing the qualities of the satisfiers is far more important than traditional studies showed us. For stations, regression analyses show that dissatisfiers are responsible for explaining almost half of the total score of the station and satisfiers are responsible for the other half of the scores passengers give for the station. We still have to put a lot of energy in getting the basics right, starting in the planning phase, but then we are not allowed to lean back. We have to keep investing in qualities like ambience, comfort and experience which makes the customers truly happy at the end of the day.

Read our paper HERE and find the presentation HERE

Supervised learning: Predicting passenger load in public transport

For many Public Transport (PT) users, overcrowding in PT vehicles has a major decreasing effect on the comfort experience. However, most online routing applications still not take comfort regarding to crowdedness into account, but provide recommendations based on shortest distance, shortest travel-time, or number of interchanges.
Being able to include certain information on crowdedness, requires knowledge about the current and future level of passenger load. Increasing amount and complexity of data describing public transport services allows us to better explore the detection methods and analysis of different phenomena of PT operations. Some countries or operators provide the possibility to use Smart Card (SC) data for occupancy prediction. However, SC data is not available in real time, which makes it hard to incorporate it into real time recommendation models. In this work, we show that it is possible to predict the passenger load via supervised learning, eliminating the need for fare collection data beyond the set needed for training.

Find the CASPT presentation by Léonie Heydenrijk-Ottens HERE

Driver schedule efficiency vs. public transport robustness: A framework to quantify this trade-off based on passive data

More complex, efficient driver schedules reduce operator costs during undisrupted operations, but increase the disruption impact for passengers and operator once a disruption occurs. We develop an integrated framework to quantify the passenger and operator costs of disruptions explicitly as function of different driver schedule schemes. Since the trade-off between driver schedule efficiency and robustness can be quantified, this supports operators in their decision-making.

Read the CASPT paper by Menno Yap HERE and find the presentation HERE

Assessing disruption management strategies in rail-bound urban public transport from a passenger perspective

This paper provides a framework for generating and assessing alternatives
in case of disruptions in rail-bound urban public transport systems,. The proposed
framework considers the passenger perspective as well as the operator perspective,
for the often-used measures of detouring and short-turning. An application of the
framework demonstrates that currently used disruption management protocols often
do not lead to the optimal solution from the passenger perspective. Furthermore, the
optimal choice between alternatives from passenger perspective shows to be
dependent on the passenger flows.

Read the CASPT paper HERE and find the presentation HERE

Passenger Route Choice and Assignment Model for Combined Fixed and Flexible Public Transport Systems

The recent technological innovations have given rise to innovative mobility solutions. Public transport systems combining such services need novel models for the design of services. We develop a multimodal route choice and assignment model for combined use of line/schedule based public transport systems (fixed public transport) and demand responsive services (flexible public transport). The model takes into account the dynamic demand-supply interaction using an iterative learning model framework. Flexible public transport can be used to perform any part of the trip, ranging from a first/last mile service to an exclusive direct door-to-door connection. The developed model is implemented in an agent based simulation framework. The model is applied to the test network of Sioux Falls. Results, in terms of modal split, fleet utilization, and passenger waiting times are analysed for scenarios in which fixed and flexible public transport are offered as competing modes as well as potential complementing modes.

Find the CASPT presentation HERE

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